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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2025, V. 22, No. 4, pp. 205-217

Parameters of long-term vegetation index dynamics as indicators of afforestation on postagrogenic lands

E.A. Terekhin 1 
1 Belgorod State National Research University, Belgorod, Russia
Accepted: 07.05.2025
DOI: 10.21046/2070-7401-2025-22-4-205-217
Natural afforestation processes are present on many postagrogenic lands of the Central Russia forest-steppe. The article describes an approach and indicators for assessing the restoration of forest vegetation on abandoned agricultural lands on the basis of parameters of long-term vegetation index dynamics. The study objects are postagrogenic lands with the same period of restoration successions. They are located on the Central Chernozem Region. The parameters of vegetation index time series, which include the Mann–Kendall tau and the linear trend slope, demonstrate different strengths of connection with the rate of natural afforestation of postagrogenic lands with deciduous and coniferous species. Differences in the rate of afforestation of abandoned lands with deciduous, coniferous and mixed composition can be expressed through the first derivative of the vegetation index function over time. The first derivative simultaneously characterizes the differences between postagrogenic lands with afforestation processes and fallow lands without them. The estimated parameters of the vegetation index long-term dynamics reflect the actual spatial, relative differences in the natural afforestation rate of postagrogenic lands in the region. They showed key spatial trends in the intensity of forest vegetation restoration on abandoned agricultural lands.
Keywords: postagrogenic lands, time series, MODIS, NDVI, natural afforestation
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References:

  1. Baisheva E. Z., Shirokikh P. S., On the bryophyte flora of abandoned agricultural lands overgrown with forest in the Republic of Bashkortostan, Izvestiya Ufimskogo nauchnogo tsentra RAN, 2017, No. 3–1, pp. 17–21 (in Russian).
  2. Bespalova E. S., Sablina O. M., Assessment of shelterbelts and erosion relief in the river basin of Vezelka (Belgorod region), Nauchnye vedomosti Belgorodskogo gosudarstvennogo universiteta. Ser.: Estestvennye nauki, 2019, V. 43, No. 3, pp. 223–231 (in Russian).
  3. Bugaev V. A., Musievskii A. L., Tsaralunga V. V., Dubravy lesostepi (Oak forests of the forest-steppe), Voronezh: Voronezhskaya gosudarstvennaya lesotekhnicheskaya akademiya, 2013, 247 p. (in Russian).
  4. Domnina E. A., Adamovich T. A., Timonov A. S., Ashikhmina T. Ya., Monitoring of overgrowing of abandoned agricultural lands using high-resolution satellite images, Teoreticheskaya i prikladnaya ehkologiya, 2022, No. 3, pp. 82–89 (in Russian), DOI: 10.25750/1995-4301-2022-3-082-089.
  5. Drozdov K. A., Elementarnye landshafty srednerusskoi lesostepi (Elementary landscapes of the Central Russian forest-steppe), Voronezh: Izd. VGU, 1991, 176 p. (in Russian).
  6. Kamyshev N. S., Khmelev K. F., Rastitel’nyi pokrov Voronezhskoi oblasti i ego okhrana (Vegetation cover of the Voronezh region and its protection), Voronezh: Izd. Voronezhskogo universiteta, 1976, 181 p. (in Russian).
  7. Karelin D. V., Lyuri D. I., Goryachkin S. V. et al., Changes in the carbon dioxide emission from soils in the course of postagrogenic succession in the chernozems forest-steppe, Eurasian Soil Science, 2015, V. 48, No. 11, pp. 1229–1241, DOI: 10.1134/S1064229315110095.
  8. Karpin V. A., Petrov N. V., Tuyunen A. V., Regeneration of forest phytocoenoses after various agricultural land use practices in the conditions of middle taiga subzone, Sibirskii lesnoi zhurnal, 2017, No. 6, pp. 120–129 (in Russian).
  9. Lisetskii F. N., Soil reproduction in steppe ecosystems of different ages, Contemporary Problems of Ecology, 2012, V. 5, No. 6, pp. 580–588, DOI: 10.1134/S1995425512060108.
  10. Medvedev A. A., Telnova N. O., Kudikov A. V., Highly detailed remote sensing monitoring of tree overgrowth on abandoned agricultural lands, Voprosy lesnoi nauki, 2019, V. 2, No. 3, pp. 1–12 (in Russian), DOI: 10.31509/2658-607X-2019-2-3-1-12.
  11. Rastitel’nost’ evropeiskoi chasti SSSR (Vegetation of the European part of the USSR). Leningrad: Nauka, 1980, 429 p. (in Russian).
  12. Solovichenko V. D., Tyutyunov S. I., Uvarov G. I., Vosproizvodstvo plodorodiya pochv i rost produktivnosti sel’skokhozyaistvennykh kul’tur Tsentral’no-Chernozemnogo regiona (Reproduction of soil fertility and growth of agricultural crop productivity in the Central Chernozem Region), Belgorod: Otchii krai, 2012, 256 p.
  13. Telesnina V. M., Postagrogenic dynamics of vegetation and soil properties during demutational succession in south taiga, Lesovedenie, 2015, No. 4, pp. 293–306 (in Russian).
  14. Terekhin E. A. (2022a), Reforestation on abandoned agricultural lands in the Central Russian forest-steppe, Izvestiya Rossiiskoi akademii nauk. Ser. geograficheskaya, 2022, V. 86, No. 4, pp. 594–604 (in Russian), DOI: 10.31857/S2587556622040112.
  15. Terekhin E. A. (2022b), Changes in intrazonal differences in the natural vegetation cover of forest-steppe landscapes in the late 20th and early 21st century, Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, V. 19, No. 1, pp. 179–192 (in Russian), DOI: 10.21046/2070-7401-2022-19-1-179-192.
  16. Trofimov I. A., Trofimova L. S., Yakovleva E. P., Preservation and optimization of agrolandscapes of the Central Chernozem zone, Izvestiya Rossiiskoi akademii nauk. Ser. geograficheskaya, 2017, No. 1, pp. 103–109 (in Russian), DOI: 10.15356/0373-2444-2017-1-103-109.
  17. Anees S. A., Mehmood K., Rehman A. et al., Unveiling fractional vegetation cover dynamics: A spatiotemporal analysis using MODIS NDVI and machine learning, Environmental and Sustainability Indicators, 2024, V. 24, Article 100485, DOI: 10.1016/j.indic.2024.100485.
  18. Bera D., Das Chatterjee N., Bera S. et al., Comparative performance of Sentinel-2 MSI and Landsat-8 OLI data in canopy cover prediction using Random Forest model: Comparing model performance and tuning parameters, Advances in Space Research, 2023, V. 71, No. 11, pp. 4691–4709, DOI: 10.1016/j.asr.2023.01.027.
  19. Gyawali A., Adhikari H., Aalto M., Ranta T., From simple linear regression to machine learning methods: Canopy cover modelling of a young forest using planet data, Ecological Informatics, 2024, V. 82, Article 102706, DOI: 10.1016/j.ecoinf.2024.102706.
  20. Heck E., de Beurs K. M., Owsley B. C., Henebry G. M., Evaluation of the MODIS collections 5 and 6 for change analysis of vegetation and land surface temperature dynamics in North and South America, ISPRS J. Photogrammetry and Remote Sensing, 2019, V. 156, pp. 121–134, DOI: 10.1016/j.isprsjprs.2019.07.011.
  21. Justice C. O., Townshend J. R. G., Vermote E. F. et al., An overview of MODIS Land data processing and product status, Remote Sensing of Environment, 2002, V. 83, No. 1–2, pp. 3–15, DOI: 10.1016/S0034-4257(02)00084-6.
  22. Khorchani M., Gaspar L., Nadal-Romero E. et al., Effects of cropland abandonment and afforestation on soil redistribution in a small Mediterranean mountain catchment, Intern. Soil and Water Conservation Research, 2023, V. 11, No. 2, pp. 339–352, DOI: 10.1016/j.iswcr.2022.10.001.
  23. Nadal-Romero E., Llena M., Cortijos-López M., Lasanta T., Afforestation after land abandonment as a nature-based solution in Mediterranean mid-mountain areas: Implications and research gaps, Current Opinion in Environmental Science and Health, 2023, V. 34, Article 100481, DOI: 10.1016/j.coesh.2023.100481.
  24. Seguini L., Vrieling A., Meroni M., Nelson A., Annual winter crop distribution from MODIS NDVI timeseries to improve yield forecasts for Europe, Intern. J. Applied Earth Observation and Geoinformation, 2024, V. 130, Article 103898, DOI: 10.1016/j.jag.2024.103898.
  25. Zhang J., Pham T.-T.-H., Kalacska M., Turner S., Using Landsat Thematic Mapper records to map land cover change and the impacts of reforestation programmes in the borderlands of southeast Yunnan, China: 1990–2010, Intern. J. Applied Earth Observation and Geoinformation, 2014, V. 31, pp. 25–36, DOI: 10.1016/j.jag.2014.01.006.
  26. Zurqani H. A., High-resolution forest canopy cover estimation in ecodiverse landscape using machine learning and Google Earth Engine: Validity and reliability assessment, Remote Sensing Applications: Society and Environment, 2024, V. 33, Article 101095, DOI: 10.1016/j.rsase.2023.101095.